The condition of perfect reconstruction of the data or input and
the there will be no dimentionality reduction is when all the \(p\) 
eigenvectors are used and \(VV^t\)  is the identity matrix. When
using large dataset features, whether it is image, text or video
data, one cannot use any machine-learning algorithms directly. In
order to reduce the training time, prepossessing steps are
required to clean the dataset. It is noted that PCA is restricted
to a linear map. Autoencoders [1]} can have non linear
encoder/decoders. A single layer autoencoder with linear function
is nearly equivalent to PCA. We use sequence-to-sequence
autoencoder in our proposed detection model.
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